Association between serum lactate and mortality in critically ill ischemic stroke patients based on MIMIC-IV data
Abstract Stroke, as an acute cerebrovascular disease, results from brain tissue damage caused by the sudden blockage or rupture of cerebral blood vessels. Ischemic stroke, a specific type of stroke, accounts for two-thirds of stroke cases leading to disability or even death, significantly impacting...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-11461-5 |
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| Summary: | Abstract Stroke, as an acute cerebrovascular disease, results from brain tissue damage caused by the sudden blockage or rupture of cerebral blood vessels. Ischemic stroke, a specific type of stroke, accounts for two-thirds of stroke cases leading to disability or even death, significantly impacting patients’ quality of life. Lactate, an indispensable substance in various physiological and pathological processes, has been utilized in predicting the prognosis of sepsis, heart failure, and acute respiratory failure. Although previous studies have evaluated the prognostic value of serum lactate at single time points, the predictive potential of dynamic lactate trajectories for all-cause mortality in patients with ischemic stroke remains unclear. Therefore, this study aims to elucidate the correlation between serum lactate concentration trajectories and all-cause mortality in patients with ischemic stroke. Information was gathered from the MIMIC-IV database, encompassing patients who had undergone a minimum of two serum lactate count assessments in the initial 7 days of ICU stay. The technique of group-based trajectory modeling (GBTM) was employed to pinpoint unique lactate counting paths. Patient classification into different trajectory categories was based on the fluctuations in their serum lactate levels throughout a specific duration. For assessing the link between serum lactate concentrations and the risk of death, survival studies were performed utilizing Kaplan–Meier curves and Cox proportional-hazards regression models. Additionally, we analyzed clinical features and the duration of hospital stays among groups defined by their trajectories to pinpoint possible variances in patient results and resource usage. The study included a cohort of 752 patients, within which two distinct trajectories of serum lactate count were identified: Class 1, characterized by an “steeper reduction of serum lactate count,” and Class 2, characterized by a “more gradual but consistent decrease of serum lactate count.” Further observation of clinical feature differences revealed that Class 2 had higher clinical evaluation index scores compared to Class 1 (SOFA, APS III, SAPS II and OASIS), and also exhibited a higher mortality rate. Subsequent Kaplan-Meier analysis demonstrated that Class 1 showed a better survival curve trend compared to Class 2 at both 28 and 90 days (all p-values less than 0.05). Additionally, further analysis using single-variable and multiple-variable Cox regression confirmed that the risk of death for Class 2 was higher than that of Class 1 at both 28 and 90 days, both in the hospital and ICU settings (hazard ratio ranges from 1.41 to 3.37, with all p-values less than 0.05). Finally, subgroup analysis identified several factors that significantly influenced trajectory classification and associated risks, including age, gender, presence of comorbidities such as diabetes, higher GCS scores and higher BMI values. This study highlights the prognostic significance of serum lactate concentration trajectories in patients with ischemic stroke. A consistent decreasing trajectory of serum lactate concentration is associated with an increased risk of mortality. Furthermore, subgroup analysis suggests that males, elder individuals, overweight or obesity people and those with diabetes are particularly noteworthy subgroups. Early identification of these clinical characteristics may aid in enhancing risk stratification and provide a basis for targeted therapeutic interventions. Future research should explore the underlying mechanistic pathways. |
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| ISSN: | 2045-2322 |